Why is AI safety so much harder than Isaac Asimov's "Three Laws of Robotics"?
The reason this is hard is because it is not trivial to understand what a law means. Many humans still have a hard time understanding laws and thus we have millions of judges and lawyers who study years to be able to even debate whether a law was broken at all.
More generally to AI, the problem of understanding laws is a byproduct of the bigger problem that AIs today do not yet have mechanisms to turn input (text, audio, other sensor data) into concepts. This is evident in even the most advanced conversation systems which struggle with dialog which is off of a particular set of subjects.
However, there are promising results with probabilistic logic programming languages that attempt to combine first-order logic with statistical inference ($\text{LP}^{\text{MLN}}$ is an example). These languages could provide, in theory, a way for future AI-lawyers (or whatever one should call them) to encode exactly what laws mean. Using this set or encoded laws, a system with a rich enough representation could determine if an action would brake a law or not. This sounds great but the &quot;rich enough representation&quot; is beyond what even today's best deep learning systems (or any other architecture) can do. For comparison, today's best deep learning systems don't even have good object permanence, something humans have around 4-7 months old. Asking those deep learning systems to also be able to represent the complexities of laws is profoundly outside of current AI capabilities.
Another promising area is only including text data and having artificial judges. This wouldn't immediately mean that AIs would obey laws but it is the start of AIs understanding the word of law.